Python - Manipulating & Analyzing Data in Pandas DataFrames
Python
| Intermediate
- 10 videos | 44m 10s
- Includes Assessment
- Earns a Badge
Explore advanced data manipulation and analysis with Pandas DataFrames, a Python library that shares similarities with relational databases. To take this course, prior basic experience is needed with Pandas DataFrames, data loading, and Jupyter Notebook data manipulation. You will learn to iterate data in your DataFrame. See how to export data to Excel files, JSON (JavaScript Object Notation) files, and CSV (comma separated values) files. Sort the contents of a DataFrame and manage missing data. Group data with a multi-index. Merge disparate data into a single DataFrame through join and concatenate operations. Finally, you will determine when and where to integrate data with structured queries, similar to SQL.
WHAT YOU WILL LEARN
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Learn how to iterate over a dataframe's rows and columns
Export the contents of a dataframe into files of various formats
Describe and apply different techniques involved in sorting the contents of a pandas dataframe
Describe and apply the different techniques involved in handling datasets where some information is missing
Implement a hierarchical index and access the dataframe's contents based on that index -
Combine two similar dataframes using the concat operation
Apply a join operation on two related but dissimilar dataframes using the merge function
Load data into a pandas dataframe from a table in a relational database
Use pandas for advanced tabular data manipulation
IN THIS COURSE
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2m 8s
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3m 24sIn this video, you will learn how to iterate over a DataFrame's rows and columns. FREE ACCESS
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3. Exporting a DataFrame3m 27sLearn how to export the contents of a DataFrame into various file formats. FREE ACCESS
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4. Sorting4m 46sUpon completion of this video, you will be able to describe and apply the different techniques involved in handling datasets where some information is missing. FREE ACCESS
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5. Handling Missing Data5m 36sUpon completion of this video, you will be able to describe and apply the different techniques involved in handling datasets where some information is missing. FREE ACCESS
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6. Grouping with a Multi-Index5m 17sIn this video, you will implement a hierarchical index and access the DataFrame's contents based on that index. FREE ACCESS
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7. Merging DataFrames3m 24sFind out how to combine two similar DataFrames using the concatenate operation. FREE ACCESS
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8. Applying Join Operations on DataFrames5m 13sFind out how to apply a join operation on two related but dissimilar DataFrames using the merge function. FREE ACCESS
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9. Pandas and Relational Databases6m 34sIn this video, you will learn how to load data into a Pandas DataFrame from a table in a relational database. FREE ACCESS
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10. Exercise: Pandas for Advanced Data Manipulation4m 20sIn this video, you will learn how to use Pandas for advanced manipulation of tabular data. FREE ACCESS
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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